Biology subjects

Mathews, C. A.

Publications and source records attributed to Mathews, C. A..

10 recordsLinked to original sources

bioRxiv2026

Heightened Distraction under Competition in Obsessive-Compulsive Disorder

The present study examine the extent to which attentional resources are allocated toward distracting affective and disorder-relevant pictures under task-relevant competition in participants with obsessive-compulsive disorder (OCD; N = 33) and controls (N = 31). Competition between cues was examined using a foreground task where participants detected coherent motion in a flickering random dot kinematogram (RDK) overlaid on pictures ranging in emotional content (pleasant, neutral, unpleasant, and OCD-evoking pictures). Steady-state visual evoked potentials (ssVEPs) were measured in response to the flickering RDK and served as an index of visuocortical engagement with task-relevant cues. Data were also fitted to the distraction under competition model (DUC), a computational framework of attention selection. Group differences emerged with stronger visuocortical distraction (attenuated task engagement) in the OCD group, driven largely by the unpleasant pictures, followed by the OCD-evoking and pleasant pictures. Furthermore, the DUC model fit well in both groups and supported the results of the univariate analysis, demonstrating the magnitude of the visuocortical distraction observed in response to the unpleasant pictures, and the presence of substantial distraction in response to the OCD-evoking pictures in the OCD group. The present findings provide visuocortical evidence of heightened distraction in response to unpleasant and OCD-evoking pictures under task-relevant competition in OCD.

neuroscience↗

bioRxiv2025

Distinct patterns of de novo coding variants contribute to Tourette Syndrome etiology

Tourette syndrome (TS) is a highly heritable childhood-onset neuropsychiatric disorder characterized by persistent motor and vocal tics. While both common and rare variants contribute to TS susceptibility, the role of rare de novo mutations (DNMs) remains incompletely characterized. Here, we report findings from the largest TS whole-exome sequencing study to date, analyzing 1,466 TS trios alongside 6,714 autism spectrum disorder (ASD) trios and 5,880 unaffected sibling controls from the Simons Simplex Collection (SSC) and SPARK cohorts. Leveraging a trio-based design across these cohorts enabled calibrated assessment of DNM burden while controlling for background mutation rates. We observed a significant exome-wide enrichment of protein-truncating DNMs in TS probands, particularly within genes intolerant to loss-of-function variation (pLI [≥] 0.9), with little contribution from damaging missense variants. Notably, TS probands did not exhibit enrichment in previously implicated ASD or developmental delay (DD) genes, but elsewhere in the genome, suggesting a distinct rare variant architecture. Using a Bayesian statistical framework that integrates both de novo and rare inherited coding variants, we identified three candidate TS risk genes with FDR [≤] 0.05: PPP5C, EXOC1, and GXYLT1. Literature shows that they have prior links to neurodevelopmental and psychiatric disorders. These findings reveal a rare variant burden in TS that is genetically distinguishable from ASD, underscore the importance of loss-of-function mutations in TS risk, and nominate novel candidate genes for future functional investigation.

neuroscience↗

bioRxiv2025

MarkerMatch: A Proximity-Based Probe-Matching Algorithm for Joint Analysis of Copy-Number Variants from Different Genotyping Arrays

MotivationCopy-number variants (CNVs) are a form of genetic structural variation with increasing importance in complex human disorders. Both DNA sequencing and microarray data can be used to call CNVs, which can be used in association tests, such as association between CNV number and disease status. Unlike genotypes, CNV detection in microarrays requires the use of observed intensity signals at each probe, which limits the imputability for analyses that span multiple array types. Thus far, a consensus set of probes (the intersection encompassing the probes that occur in common on all arrays) has been used to circumvent the problem of differing array-specific sensitivities. This has, however, led to excessive reduction in overall sensitivity of CNV calls as arrays can have an undesirably low overlap of probe sets. To overcome this limitation, we developed MarkerMatch, a proximity-based algorithm that matches probes across different genotyping microarrays to maximize the number of probes considered in the CNV calling algorithm, thereby increasing the resolution and sensitivity while preserving precision. ResultsBy analyzing CNV calls from 4,906 individuals genotyped across three different arrays (Global Screening Array, Omni2.5 array, and Omni Express Exome array), we show that the MarkerMatch approach improves sensitivity by increasing the density of probes available for CNV calling while maintaining precision or improving it relative to the current practice (e.g., use of consensus probes only). We further demonstrate that MarkerMatch exceeds the output from current practice in terms of F1 score, Fowlkes-Mallows index, and Jaccard index. We also optimize MarkerMatch parameters, DMAX and Method, and find an optimal DMAX setting at 10kb, with no clear optimal candidate based on Method, indicating that parameters for this metric should be determined on a use case basis.

bioinformatics↗

bioRxiv2020

Examining sex-differentiated genetic effects across neuropsychiatric and behavioral traits

BackgroundThe origin of sex differences in prevalence and presentation of neuropsychiatric and behavioral traits is largely unknown. Given established genetic contributions and correlations across these traits, we tested for a sex-differentiated genetic architecture within and between traits. MethodsUsing genome-wide association study (GWAS) summary statistics for 20 neuropsychiatric and behavioral traits, we tested for differences in SNP-based heritability (h2) and genetic correlation (rg<1) between sexes. For each trait, we computed z-scores from sex-stratified GWAS regression coefficients and identified genes with sex-differentiated effects. We calculated Pearson correlation coefficients between z-scores for each trait pair, to assess whether specific pairs share variants with sex-differentiated effects. Finally, we tested for sex differences in between-trait genetic correlations. ResultsWith current sample sizes (and power), we found no significant, consistent sex differences in SNP-based h2. Between-sex, within-trait genetic correlations were consistently high, although significantly less than 1 for educational attainment and risk-taking behavior. We identified genome-wide significant genes with sex-differentiated effects for eight traits. Several trait pairs shared sex-differentiated effects. The top 0.1% of genes with sex-differentiated effects across traits overlapped with neuron- and synapse-related gene sets. Most between-trait genetic correlation estimates were similar across sex, with several exceptions (e.g. educational attainment & risk-taking behavior). ConclusionsSex differences in the common autosomal genetic architecture of neuropsychiatric and behavioral phenotypes are small and polygenic, requiring large sample sizes. Genes with sex-differentiated effects are enriched for neuron-related gene sets. This work motivates further investigation of genetic, as well as environmental, influences on sex differences.

genetics↗

bioRxiv2019

Cross-disorder GWAS meta-analysis for Attention Deficit/Hyperactivity Disorder, Autism Spectrum Disorder, Obsessive Compulsive Disorder, and Tourette Syndrome

Attention Deficit/Hyperactivity Disorder (ADHD), Autism Spectrum Disorder (ASD), Obsessive-Compulsive Disorder (OCD), and Tourette Syndrome (TS) are among the most prevalent neurodevelopmental psychiatric disorders of childhood and adolescence. High comorbidity rates across these four disorders point toward a common etiological thread that could be connecting them across the repetitive behaviors-impulsivity-compulsivity continuum. Aiming to uncover the shared genetic basis across ADHD, ASD, OCD, and TS, we undertake a systematic cross-disorder meta-analysis, integrating summary statistics from all currently available genome-wide association studies (GWAS) for these disorders, as made available by the Psychiatric Genomics Consortium (PGC) and the Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH). We present analysis of a combined dataset of 93,294 individuals, across 6,788,510 markers and investigate associations on the single-nucleotide polymorphism (SNP), gene and pathway levels across all four disorders but also pairwise. In the ADHD-ASD-OCD-TS cross disorder GWAS meta-analysis, we uncover in total 297 genomewide significant variants from six LD (linkage disequilibrium) -independent genomic risk regions. Out of these genomewide significant association results, 199 SNPs, that map onto four genomic regions, show high posterior probability for association with at least three of the studied disorders (m-value>0.9). Gene-based GWAS meta-analysis across ADHD, ASD, OCD, and TS identified 21 genes significantly associated under Bonferroni correction. Out of those, 15 could not be identified as significantly associated based on the individual disorder GWAS dataset, indicating increased power in the cross-disorder comparisons. Cross-disorder tissue-specificity analysis implicates the Hypothalamus-Pituitary-Adrenal axis (stress response) as possibly underlying shared pathophysiology across ADHD, ASD, OCD, and TS. Our work highlights genetic variants and genes that may contribute to overlapping neurobiology across the four studied disorders and highlights the value of re-defining the framework for the study across this spectrum of highly comorbid disorders, by using transdiagnostic approaches.

genetics↗

bioRxiv2019

Genetic overlap between obsessive-compulsive disorder, related symptoms in the population and insulin signaling: etiological implications

ObjectiveObsessive-compulsive symptoms (OCS) in the population have been linked to obsessive-compulsive disorder (OCD) in genetic and epidemiological studies. Insulin signaling has been implicated in OCD. We extend previous work by assessing genetic overlap between OCD, population-based OCS, and central nervous system (CNS) and peripheral insulin signaling.\n\nMethodsWe conducted genome-wide association studies (GWASs) in the population-based Philadelphia Neurodevelopmental Cohort (PNC, 650 children and adolescents) of the total OCS score and six OCS factors from an exploratory factor analysis of 22 questions. Subsequently, we performed polygenic risk score (PRS) analysis to assess shared genetic etiologies between clinical OCD (using GWAS data from the Psychiatric Genomics Consortium), the total OCS score and OCS factors. We then performed gene-set analyses with a set of OCD-linked genes centered around CNS insulin-regulated synaptic function and PRS analyses for five peripheral insulin signaling-related traits. For validation purposes, we explored data from the independent Spit for Science population cohort (5047 children and adolescents).\n\nResultsIn the PNC, we found a shared genetic etiology between OCD and impairment, contamination/cleaning and guilty taboo thoughts. In the Spit for Science cohort, we were able to validate the finding for contamination/cleaning, and additionally observed genetic sharing between OCD and symmetry/counting/ordering. The CNS insulin-linked gene-set associated with symmetry/counting/ordering. We also identified genetic sharing between peripheral insulin signaling-related traits (type 2 diabetes and the blood levels of HbA1C, fasting insulin and 2 hour glucose) and OCD as well as certain OCS.\n\nConclusionsOCD, OCS in the population and insulin-related traits share genetic risk factors, indicating a common etiological mechanism underlying somatic and psychiatric disorders.

genetics↗

bioRxiv2018

Concordance Of Genetic Variation That Increases Risk For Tourette Syndrome And That Influences Its Underlying Neurocircuitry

BACKGROUNDThere have been considerable recent advances in understanding the genetic architecture of Tourette Syndrome (TS) as well as its underlying neurocircuitry. However, the mechanisms by which genetic variations that increase risk for TS - and its main symptom dimensions - influence relevant brain regions are poorly understood. Here we undertook a genome-wide investigation of the overlap between TS genetic risk and genetic influences on the volume of specific subcortical brain structures that have been implicated in TS.\n\nMETHODSWe obtained summary statistics for the most recent TS genome-wide association study (GWAS) from the TS Psychiatric Genomics Consortium Working Group (4,644 cases and 8,695 controls) and GWAS of subcortical volumes from the ENIGMA consortium (30,717 individuals). We also undertook analyses using GWAS summary statistics of key symptom factors in TS, namely social disinhibition and symmetry behaviour. SNP Effect Concordance Analysis (SECA) was used to examine genetic pleiotropy - the same SNP affecting two traits - and concordance - the agreement in SNP effect directions across these two traits. In addition, a conditional false discovery rate (FDR) analysis was performed, conditioning the TS risk variants on each of the seven subcortical and the intracranial brain volume GWAS. Linkage Disequilibrium Score Regression (LDSR) was used as validation of SECA.\n\nRESULTSSECA revealed significant pleiotropy between TS and putaminal (p=2x10-4) and caudal (p=4x10-4) volumes, independent of direction of effect, and significant concordance between TS and lower thalamic volume (p=1x10-3). LDSR lent additional support for the association between TS and thalamic volume (p=5.85x10-2). Furthermore, SECA revealed significant evidence of concordance between the social disinhibition symptom dimension and lower thalamic volume (p=1x10-3), as well as concordance between symmetry behaviour and greater putaminal volume (p=7x10-4). Conditional FDR analysis further revealed novel variants significantly associated with TS (p<8x10-7) when conditioning on intracranial (rs2708146, q=0.046; and rs72853320, q=0.035 and hippocampal (rs1922786, q=0.001 volumes respectively.\n\nCONCLUSIONThese data indicate concordance for genetic variations involved in disorder risk and subcortical brain volumes in TS. Further work with larger samples is needed to fully delineate the genetic architecture of these disorders and their underlying neurocircuitry.

genomics↗

bioRxiv2017

Examination of the Shared Genetic Basis of Anorexia Nervosa and Obsessive-Compulsive Disorder

Anorexia nervosa (AN) and obsessive-compulsive disorder (OCD) are often comorbid and likely to share genetic risk factors. Hence, we examine their shared genetic background using a crossdisorder GWAS meta-analysis of 3,495 AN cases, 2,688 OCD cases and 18,013 controls. We confirmed a high genetic correlation between AN and OCD (rg = 0.49 {+/-} 0.13, p = 9.07x10-7) and a sizable SNP heritability (SNP h2 = 0.21 {+/-} 0.02) for the cross-disorder phenotype. Although no individual loci reached genome-wide significance, the cross-disorder phenotype showed strong positive genetic correlations with other psychiatric phenotypes (e.g., bipolar disorder, schizophrenia, neuroticism) and negative correlations with metabolic phenotypes (e.g., BMI, triglycerides). Follow-up analyses revealed that although AN and OCD overlap heavily in their shared risk with other psychiatric phenotypes, the relationship with metabolic and anthropometric traits is markedly stronger for AN than for OCD. We further tested whether shared genetic risk for AN/OCD was associated with particular tissue or cell-type gene expression patterns and found that the basal ganglia and medium spiny neurons were most enriched for AN/OCD risk, consistent with neurobiological findings for both disorders. Our results confirm and extend genetic epidemiological findings of shared risk between AN and OCD and suggest that larger GWASs are warranted.

genetics↗

bioRxiv2017

Psychiatric Genomics: An Update and an Agenda

The Psychiatric Genomics Consortium (PGC) is the largest consortium in the history of psychiatry. In the past decade, this global effort has delivered a rapidly increasing flow of new knowledge about the fundamental basis of common psychiatric disorders, particularly given its dedication to rapid progress and open science. The PGC has recently commenced a program of research designed to deliver \"actionable\" findings - genomic results that (a) reveal the fundamental biology, (b) inform clinical practice, and (c) deliver new therapeutic targets. This is the central idea of the PGC: to convert the family history risk factor into biologically, clinically, and therapeutically meaningful insights. The emerging findings suggest that we are entering into a phase of accelerated translation of genetic discoveries to impact psychiatric practice within a precision medicine framework.\n\nCollaboratorsPGC Coordinating Committee: Mark Daly, Michael Gill, John Kelsoe, Karestan Koenen, Douglas Levinson, Cathryn Lewis, Ben Neale, Danielle Posthuma, Jonathan Sebat, and Pamela Sklar.

genetics↗

bioRxiv2017

Evolutionary and functional data power search for obsessive-compulsive disorder genes

Obsessive-compulsive disorder (OCD) is a severe psychiatric disorder linked to abnormalities in the cortico-striatal circuit and in glutamate signaling. We sequenced coding and regulatory elements for 608 genes implicated in OCD from humans and two animal models (mouse and dog). Using a new method, PolyStrat, which prioritizes variants disrupting evolutionarily conserved, functional regions, we found four strongly associated genes when comparing 592 cases to 560 controls. These results were validated in a second, larger cohort. NRXN1 and HTR2A are enriched for coding variants altering postsynaptic protein-binding domains, while CTTNBP2 (synapse maintenance) and REEP3 (vesicle trafficking) are enriched for regulatory variants. The rare coding variant burden in NRXN1 achieves genomewide significance (p=6.37x10-11) when we include public data for 33,370 controls. Of 17 regulatory variants identified in CTTNBP2 and REEP3, we show that at least six alter transcription factor-DNA binding in human neuroblastoma cells. Our findings suggest synaptic adhesion as a key function in compulsive behaviors across three species, and demonstrate how combining targeted sequencing with functional annotations can identify potentially causative variants in both coding and noncoding regions, even when genomic data is limited.

genomics↗